Enda Howley

Associate Professor

Ollscoil na Gaillimhe – University of Galway

Ireland

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About

Enda Howley is an Associate Professor at Ollscoil na Gaillimhe – University of Galway, Ireland. His research focuses on multi-objective reinforcement learning, energy-efficient virtual machine consolidation, and the application of genetic programming in multi-agent systems. Recent publications highlight his work on COVID-19 mitigation strategies and advanced modeling techniques in cellular dynamics.

Articles (11)

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2024

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2023

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2022

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2022

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2022

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2022

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2022

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2022

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2020

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2020

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2020

Collaborators (6)

Eugenio Bargiacchi

Vrije Universiteit Brussel

BELGIUM

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Florence Abram

Lecturer

National University of Ireland Galway

IRELAND

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Roxana Rădulescu

Vrije Universiteit Brussel

BELGIUM

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Eoin McEvoy

Assistant Professor

University of Galway

IRELAND

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Patrick Mannion

Lecturer in Computer Science

National University of Ireland Galway

IRELAND

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Jim Duggan

University of Galway

IRELAND

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Enda Howley

Research Interests

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About

Articles (11)

Exploring the Pareto front of multi-objective COVID-19 mitigation policies using reinforcement learning

A Genetic Programming-based Framework for Semi-automated Multi-agent Systems Engineering

A Practical Guide to Multi-Objective Reinforcement Learning and Planning

Thermodynamically-motivated chemo-mechanical models and multicellular simulation to provide new insight into active cell and tumour remodelling

Applying neural networks to predict HPC-I/O bandwidth over seismic data on lustre file system for ExSeisDat

Expected scalarised returns dominance: a new solution concept for multi-objective decision making

Applying Reinforcement Learning towards automating energy efficient virtual machine consolidation in cloud data centers

The impact of noise and missing fragmentation cleavages on de novo peptide identification algorithms

Stock‐flow thinking: A difficult concept to grasp

An intelligent ensemble learning approach for energy efficient and interference aware dynamic virtual machine consolidation

Dynamic virtual machine consolidation using a multi-agent system to optimise energy efficiency in cloud computing

Collaborators (6)

Eugenio Bargiacchi

Florence Abram

Roxana Rădulescu

Eoin McEvoy

Patrick Mannion

Jim Duggan

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